R2R is a dataset for visually-grounded natural language navigation in real buildings. The dataset requires autonomous agents to follow human-generated navigation instructions in previously unseen buildings, as illustrated in the demo above. For training, each instruction is associated with a Matterport3D Simulator trajectory. 22k instructions are available, with an average length of 29 words. There is a test evaluation server for this dataset available at EvalAI.
144 PAPERS • 2 BENCHMARKS
The HELP dataset is an automatically created natural language inference (NLI) dataset that embodies the combination of lexical and logical inferences focusing on monotonicity (i.e., phrase replacement-based reasoning). The HELP (Ver.1.0) has 36K inference pairs consisting of upward monotone, downward monotone, non-monotone, conjunction, and disjunction.
28 PAPERS • 1 BENCHMARK
Talk The Walk is a large-scale dialogue dataset grounded in action and perception. The task involves two agents (a “guide” and a “tourist”) that communicate via natural language in order to achieve a common goal: having the tourist navigate to a given target location.
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IQUAD is a dataset for Visual Question Answering in interactive environments. It is built upon AI2-THOR, a simulated photo-realistic environment of configurable indoor scenes with interactive object. IQUAD V1 has 75,000 questions, each paired with a unique scene configuration.
6 PAPERS • NO BENCHMARKS YET
Talk2Nav is a large-scale dataset with verbal navigation instructions.
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